Acquisition of a biped walking pattern using a poincare map

被引：0

作者：

Morimoto, J ^{[1
]}

Nakanishi, J ^{[1
]}

Endo, G ^{[1
]}

Cheng, G ^{[1
]}

Atkeson, CG ^{[1
]}

Zeglin, G ^{[1
]}

机构：

[1] ATR Computat Neurosci Lab, JST, ICORP, Computat Brain Project, Kyoto 6100288, Japan

来源：

2004 4TH IEEE/RAS INTERNATIONAL CONFERENCE ON HUMANOID ROBOTS, VOLS 1 AND 2, PROCEEDINGS | 2004年

关键词：

biped walking; reinforcement learning; Poincare map;

D O I：

暂无

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

We propose a model-based reinforcement learning algorithm for biped walking in which the robot learns to appropriately place the swing leg. This decision is based on a learned model of the Poincare map of the periodic walking pattern. The model maps from a state at a single support phase and foot placement to a state at the next single support phase. We applied this approach to both a simulated robot model and an actual biped robot. We show that successful walking patterns are acquired.

引用

页码：912 / 924

页数：13

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